In a wireless communication system, a transmitting end and a receiving end obtain a higher rate by using a plurality of antennas in a spatial multiplexing mode. Compared with a common spatial multiplexing mode, an enhanced technique is that the receiving end feeds back channel state information (CSI) to the transmitting end and the transmitting end uses some transmission precoding techniques according to the obtained channel state information to greatly improve transmission performance. For Single-User Multi-input Multi-output (MIMO), channel characteristic vector information is directly used for precoding; and for Multi-User MIMO, more accurate channel state information is needed. In some techniques such as in LTE of 4G, 802.16m standard specification, feedback of channel state information mainly utilizes a simpler single-codebook feedback way, while the performance of the transmission precoding technique of MIMO is more dependent on the accuracy of codebook feedback. Here, the basic principle of the channel state information quantization feedback based on a codebook is simply set forth below: supposing that limited feedback channel capacity is B bps/Hz, the number of available code words is N=2B. A characteristic vector space of a channel matrix forms a codebook space ={F1, F2 . . . , after quantization, the transmitting end and the receiving end both save or generate the codebook (the codebook in the receiving end/transmitting end is the same) in real time. The receiving end obtains a channel matrix H, selects a code word {circumflex over (F)}i which most matches a channel from the codebook space  in accordance with a certain criterion, and feeds back a code word sequence number i of the code word to the transmitting end, herein the code word sequence number is called as a Precoding Matrix Indicator (PMI); and the transmitting end finds the corresponding precoding code word {circumflex over (F)}i according to the sequence number i and thus obtains the channel state information, herein {circumflex over (F)}i denotes characteristic vector information of the channel.
With the high-speed development of the wireless communication technology, wireless applications of users are increasingly rich, thereby driving the quick increase of wireless data services. It is predicted that, within the next 10 years, data services increase at a rate of 1.6 to 2 times per year, which would bring a huge challenge to wireless access networks. A multi-antenna technique is a key technique for coping with explosive increase challenge of wireless data services. At present, the multi-antenna technique supported in 4G is a horizontal-dimension beam forming technology which only supports 8 ports at most, and there is a greater potential to further greatly improve system capacity.
Evolution of the multi-antenna technique is performed mainly around several targets as follows: (1) higher beam forming/precoding gains; (2) more space multiplexing layers (MU and SU), and smaller interlayer interference; (3) more overall coverage; and (4) smaller interference between sites. Massive MIMO and 3D MIMO are two main candidate techniques for MIMO evolution in the next generation wireless communication. For a system based on a Massive MIMO technique, it is mainly characterized in that a transmitting end side is configured with a massive antenna array, for example, 100 antennas or even more, and during data transmission, multiple users are multiplexed simultaneously at the same frequency by using the Multi-User Multi-input Multi-output (MU-MIMO) technique. It can be proved that, no matter whether it is a strongly-correlative channel in a line-of-sight environment or a non-correlative channel under a rich scattering environment, a correlation coefficient between channels of any two users is exponentially attenuated with the increase of the number of the antennas. For example, when the transmitting end side is configured with 100 antennas, the correlation coefficient between the channels of any two users is approximately 0, i.e., corresponding channels of multiple users are approximately orthogonal. In another aspect, a massive array can bring very considerable array gains and diversity gains. The main technical feature of 3D MIMO lies in that, beam forming capabilities are very good in both a vertical dimension and a horizontal dimension. Due to the limitation on antenna size, there is little possibility to place more than a hundred of antennas in one dimension. Therefore, in most application scenarios, when the Massive MIMO technology is applied, the 3D MIMO is generally used in a combined manner.
For Massive MIMO, due to the introduction of massive antennas, the traditional method is that each antenna transmits a Channel State Information-Reference Signal (CSI-RS), and a receiving end detects the CSI-RS, obtains a channel matrix corresponding to each transmission resource through channel estimation, obtains an optimal precoding vector of each frequency-domain sub-band on a base band and optimal transmission layer number information of a broadband according to the channel matrix, and then performs a feedback based on the above introduced codebook feedback technique. This method has a greater problem during application in Massive MIMO, which is mainly embodied as follows: pilot overhead can increase with the increase of the transmitting antenna number and is very huge when the number of antennas is large. In addition, since the codebook used during feedback needs to contain a great many code words, it is very difficult to select the code words, and a very great complexity is caused to the receiving end and there is almost no possibility to implement, or a huge cost needs to be spent. Moreover, the overhead for codebook feedback is so great that the feedback link overhead is huge. Therefore, generally a better method for Massive MIMO is to use a beam selection technique or a beam training technique to obtain an optimum beam forming precoding weight, herein the beam forming precoding weight can be used to perform weighting and forming on radio frequency signals in time-domain to form beams, such that energy is more concentrated.
Some basic principles of beam forming and beam selection techniques are described below. A transmitting end sends a plurality of pilot beams that are subjected to beam forming, herein, generally transmitting beam forming can also be referred to as precoding, or transmitting weighting processing, such pilot beams are formed after weighting and combining transmission signals on a plurality of antenna and correspond to a plurality of transmitting antenna. The binding relationship between a sending resource position of a plurality of Pilot Beams and the number of pilots (Beam ID) can be learned from signaling configurations or agreements made in advance with receiving and transmitting ends. The receiving end detects transmitting positions of a plurality of Pilot Beams, selects one or more stronger beams, and informs the transmitting end through uplink feedback. The transmitting end performs beam forming on data transmission based on a beam forming weight on the pilot in accordance with feedback information of the receiving end.
In order to save pilot overhead and improve feedback efficiency, beam selection can be further extended to a secondary beam selection. Pilot Beam can be further divided into Sector Beam (a first stage beam pilot, a coarse beam) and Finer Beam (a second stage beam pilot, a narrow beam). The transmitting end first transmits Sector Beam and the receiving end selects the best Sector Beam, then the transmitting end transmits Finer Beam included in the Sector Beam, and the receiving end feeds back information of the best Finer Beam. The transmitting end performs beam forming based on the information fed back by the receiving end. In addition to the feature in which the transmitting end system can send beam pilots to perform selection and training of downlink forming weights, the receiving end can also transmit beam pilots to perform selection and training of uplink forming weights. A solution similar to the downlink beam selection technique can be used to acquire uplink channel information.
In an ideal TDD system, when the uplink and downlink reciprocity is available, generally, an uplink optimum precoding weight can be obtained by transmitting downlink pilots through reciprocity, and a downlink optimum precoding weight can be obtained by transmitting uplink pilots through reciprocity. However, for a FDD system or a TDD system with poor reciprocity, in the related art, if large-scale antennas are employed for both uplink and downlink, the above-described beam selection technique is required to be employed for both receiving and transmitting ends for performing transmission of a plurality of beam pilots and then performing beam selection. For the downlink, these beam pilots can be shared to some extent because the transmitting end services a plurality of user terminal, although the number of beams has a certain effect on overhead, the influence is small. However, for the user terminal UE, due to the large number and the fact that each UE transmits a plurality of beams for selection by a base station, significant pilot overhead of uplink will be thus caused, thereby severely influencing the system's effective resource utilization.
Therefore, how to reduce uplink pilot overhead in FDD system or in other communication systems with poor reciprocity becomes an important subject.